Courses

Currently, all of our training courses are being held online.

All of our courses are hosted by expert certified trainers and research professionals who teach through a mix of demonstrative and practical sessions to provide high-class, practical training.

You can register for our courses online. To discuss any of our courses or specific training requirements, please call +44 (0) 20 8697 3377 .

An Introduction to Machine Learning using Stata, Co-Developed with Lancaster University

26 - 27 October 2020 Online 2 days (26th October 2020 - 27th October 2020) Stata

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

Recent years have witnessed an unprecedented availability of information on social, economic, and health-related phenomena. Researchers, practitioners, and policymakers have nowadays access to huge datasets (the so-called “Big Data”) on people, companies and institutions, web and mobile devices, satellites, etc., at increasing speed and detail.

Causal Inference using Stata

10th August 2020 (9am-11am & 12pm-2pm, Eastern Standard Time) Online 1 day (10th August 2020 - 10th August 2020) Stata

Presented By: Dr. Austin Nichols

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Participants will be introduced to Stata and causal inference using practical examples. The fundamentals of data analysis and visualization will also be taught, using appropriate Stata commands and programming techniques

Macroeconomic Density Forecasting & Nowcasting

10 - 11 Aug 2020 (10-12pm & 2-4pm London time) Online 2 days (10th August 2020 - 11th August 2020) EViews

Presented By: Dr. Andrea Carriero (Queen Mary, University of London)

Whether you deal with forecasting at a Central Bank, public institution, bank or consultancy firm; or you use forecasting techniques in your research, this is the perfect course to bring you up to date with the latest methods in the forecasting profession.

Introduction to Panel Data Analysis with Stata

13 - 14 August (8 hours, 2020) Online 2 days (13th August 2020 - 14th August 2020) Stata

Presented By: Dr. Malvina Marchese (CASS Business School, London)

Our web-based 'Introduction to Panel Data Analysis with Stata' course provides an overview of the most-used panel data techniques and is ideal for the beginner/intermediate-level user who wants to learn how to implement panel data estimation with Stata commands.

How to Write Your Dissertation with Stata

17 - 18 August 2020 Online 2 days (17th August 2020 - 18th August 2020) Stata

The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.

Participants will receive a free temporary Stata license, as well as a recording of the training session, that will be live for 30 days.

The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of Stata is required.

  • How to structure your dissertation
  • Abstract and introduction in depth discussion and examples
  • How to get a smart literature review –discussion of successful examples
  • Build, estimate and forecast from linear regression, time series and panel models using STATA
  • Understand and critically present and discuss your results

Do you have course specific questions? Email our team info@timberlake.co.uk. If you have course content specific questions, you are welcome to reach out to the course tutor here: malvinamarchese@timberlake.co.uk.

How to Write your Dissertation with EViews

19 - 20 Aug 2020 Online 2 days (19th August 2020 - 20th August 2020) EViews

The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Eviews to obtain any required econometrics.

Participants will receive a free temporary EViews license, as well as a recording of the training session, that will be live for 30 days.

The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of EViews is required.

  • How to structure your dissertation
  • Abstract and introduction in depth discussion and examples
  • How to get a smart literature review: discussion of successful examples
  • Build, estimate and forecast from linear regression, time series and panel data models using EViews
  • Understand and critically present and discuss your results

Stata Programming Workshop: Introduction and Advanced

3 & 4, 8 & 9 September 2020 Online 4 days (3rd September 2020 - 9th September 2020) Stata

Presented by Prof. Christopher F Baum, Boston College, USA and Dr. Malvina Marchese, Cass Business School, London

This course will be delivered as an online webinar, via Zoom.

This course is taught in two sections. The first, is for Stata users–professionals and researchers from all academic disciplines–who would like to use Stata programming techniques to enhance the efficiency and reliability of their research. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to use do-file programming techniques effectively, including topics such as local and global macros, r-returns and e-returns, implicit and explicit loops and debugging techniques.

The second, is for users who have completed the companion course Introduction to Stata Programming and would like to use more advanced features of the Stata and Mata programming languages. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.

Stata Programming Workshop

15 - 17 June 2020 New Horizons, Computer Learning Centre, New York City, USA 3 days (3rd September 2020 - 9th September 2020) Stata

Presented By: Professor Christopher F. Baum

Stata Programming Workshop is an opportunity for graduate students, academics, researchers and professionals to expand their knowledge of Stata. This 3-day course introduces programming skills to those who have never written a program in Stata.

Time series Analysis with Stata

14 - 15 September 2020 Online 2 days (14th September 2020 - 15th September 2020) Stata

The aim of this course is to provide participants with an in-depth understanding of the fundamental concepts of time series modelling and forecasting and with the practical skills to use Stata to model and forecast economic time series.

This comprehensive webinar is hosted through Zoom and runs over a total of 9 hours, with 4 hours each day (2 in the morning and 2 in the afternoon) with an extra Q&A session on the second day.

Advances in Causal Inference using Stata

14 & 15 September 2020 Online 2 days (14th September 2020 - 15th September 2020) Stata

Presented By: Dr. Giovanni Cerulli, IRCrES-CNR

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

Introduction to Panel Data Analysis with Stata

18 - 19 September (8 hours, 2020) Online 2 days (18th September 2020 - 19th September 2020) Stata

Presented By: Dr. George Naufal (Texas A&M University)

Our web-based 'Introduction to Panel Data Analysis with Stata' course provides an overview of the most-used panel data techniques and is ideal for the beginner/intermediate-level user who wants to learn how to implement panel data estimation with Stata commands.

Machine Learning with Eviews

25-26 September 2020 Online 2 days (25th September 2020 - 26th September 2020) EViews

Presented by: Lecturer/s Malvina Marchese , Cass Business School , London

Machine learning is a relatively new approach to data analytics, which places itself in the intersection between statistics, computer science, and artificial intelligence. Its primary objective is that of turning information into knowledge and value by “letting the data speak”. To this purpose, machine learning limits prior assumptions on data structure, and relies on a model-free philosophy supporting algorithm development, computational procedures and analytical solutions. Computationally, machine learning was unfeasible a few years ago, it is a product of the computerised era, of today's machines' computing power and ability to learn. It is also a product of hardware development and continuous software upgrading. This course is a primer to machine learning techniques in Eviews.

The latest edition of Eviews 11 offers various packages to perform machine learning. After the course, participants are expected to have an improved understanding of EViews' potential to perform some of the most used machine learning techniques, thus becoming able to master research tasks and specifically to master model selection techniques.

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